整合基因组学对了解宿主与病原体之间的相互作用非常重要。

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS
Priyanka Mehta, Aparna Swaminathan, Aanchal Yadav, Partha Chattopadhyay, Uzma Shamim, Rajesh Pandey
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引用次数: 0

摘要

传染病是全球发病和死亡的主要原因。致病微生物的基因组很容易发生变异,导致疾病爆发,给医疗保健和医疗支持带来挑战。了解某些症状在临床上是如何表现出来的,对于治疗决策和疫苗疗效/保护至关重要。值得注意的是,感染病原体、宿主反应和微生物共存之间的相互作用会影响疾病的发展轨迹和临床结果。观察到的无症状患者(轻度、中度和重度)和无症状感染的范围突出了了解驱动保护/易感性因素的挑战和潜力。随着高通量工具(如最先进的多组学分析和下一代测序)的不断增加,与异质性疾病表现相关因素的遗传驱动因素可以同步进行研究。然而,这种策略在有效整合宿主与病原体的相互作用方面并非没有局限性。尽管如此,采用综合基因组学方法(例如 RNA 测序数据)探索宿主-病原体相互作用的多层次复杂性,可能是纳入高通量数据研究结果的另一种方法。我们进一步提出,基于全转录组的技术可用于捕捉转录活跃的微生物单元,以阐明功能微生物组。因此,我们从整体角度探讨了研究方法,这些方法可以利用相同的基因组数据来研究宿主与病原体相互作用的多个看似独立但又深度关联的功能域,这些功能域会调节疾病的严重程度和临床结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Integrative genomics important to understand host-pathogen interactions.

Infectious diseases are the leading cause of morbidity and mortality worldwide. Causative pathogenic microbes readily mutate their genome and lead to outbreaks, challenging the healthcare and the medical support. Understanding how certain symptoms manifest clinically is integral for therapeutic decisions and vaccination efficacy/protection. Notably, the interaction between infecting pathogens, host response and co-presence of microbes influence the trajectories of disease progression and clinical outcome. The spectrum of observed symptomatic patients (mild, moderate and severe) and the asymptomatic infections highlight the challenges and the potential for understanding the factors driving protection/susceptibility. With the increasing repertoire of high-throughput tools, such as cutting-edge multi-omics profiling and next-generation sequencing, genetic drivers of factors linked to heterogeneous disease presentations can be investigated in tandem. However, such strategies are not without limits in terms of effectively integrating host-pathogen interactions. Nonetheless, an integrative genomics method (for example, RNA sequencing data) for exploring multiple layers of complexity in host-pathogen interactions could be another way to incorporate findings from high-throughput data. We further propose that a Holo-transcriptome-based technique to capture transcriptionally active microbial units can be used to elucidate functional microbiomes. Thus, we provide holistic perspective on investigative methodologies that can harness the same genomic data to investigate multiple seemingly independent but deeply interconnected functional domains of host-pathogen interaction that modulate disease severity and clinical outcomes.

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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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